🚀 About Me

I am an AI/ML Engineer with over 3 years of experience bridging the gap between Deep Learning research and production deployment. Currently, I focus on Computer Vision, Generative AI (GANs), and optimizing models for Edge devices.

• 🔭 Currently working on: Building scalable Video Recognition Pipelines for real-time action detection.
• 💡 Specialization:
  • Core Vision: End-to-end development of Object Detection, Semantic Segmentation, & Pose Estimation systems.
  • Edge Optimization: Accelerating inference on NVIDIA Jetson using TensorRT & ONNX.
  • Generative AI: Leveraging GANs for synthetic data generation and defect synthesis.
• 🌱 Interest: Reinforcement Learning, Generative AI (LLMs & RAG), Advanced Computer Vision, and Robotics perception.

🛠️ Technical Stack

| Domain | Technologies | | :--- | :--- | | Languages | | | AI & CV | | | Edge & MLOps | | | Tools | |

🔭 Featured Work

🏭 Defect Generation & Segmentation (GANs)

Developed a pipeline to generate 10K+ synthetic defect images to solve data scarcity in manufacturing.

• Impact: Reduced manual inspection time by 30% and improved detection accuracy to 92%.
• Tech: Python, PyTorch, CycleGAN, Lama, OpenCV.

🏎️ Autonomous Vehicle Perception Stack

Engineered a real-time segmentation system for off-road autonomous vehicles on Edge hardware.

• Impact: Achieved 95% IoU for drivable area detection and 30+ FPS on NVIDIA Jetson Orin AGX.
• Tech: NVIDIA Jetson, TensorRT, ONNX, Docker, CI/CD.

📚 Publications

I am a published researcher in the field of Computer Vision for Healthcare.

1. Deep Learning Algorithm for Identification of Ear Disease
   • Springer (2022) | Link to Paper
2. Detection and identification of COVID-19 based on chest medical images
   • International Journal of Intelligent Networks | Link to Paper

📊 GitHub Stats